Regional and demographic variations of Carotid artery Intima and Media Thickness (CIMT): A Systematic review and meta-analysis

Background and objective Carotid artery intima media thickness (CIMT) is a strong predictor of Coronary Heart Disease (CHD) and independent phenotype of early atherosclerosis. The global variation of CIMT and its demographic association is yet unclear. We evaluated regional variations of CIMT based on WHO regions and assessed the differences by age and sex. Methods A systematic search was conducted on studies published between 1980 January up to December 2020. PubMed, Oxford Medicine Online, EBSCO, Taylor & Francis, Oxford University Press and Embase data bases were used for searching. Supplementary searches were conducted on the Web of Science and Google Scholar. Grey literature was searched in “Open Grey” website. The two major criteria used were “adults” and “carotid intima media”. The search strategy for PubMed was created first and then adapted for the Oxford Medicine Online, EBSCO, Taylor & Francis, Oxford University Press and Embase databases. Covidence software (Veritas Health Innovation, Melbourne, Australia; http://www.covidence.org) was used to manage the study selection process. Meta-analyses were done using the random-effects model. An I2 ≥ 50% or p< 0:05 were considered to indicate significant heterogeneity. Results Of 2847 potential articles, 46 eligible articles were included in the review contributing data for 49 381 individuals (mean age: 55.6 years, male: 55.8%). The pooled mean CIMT for the non-CHD group was 0.65mm (95%CI: 0.62–0.69). There was a significant difference in the mean CIMT between regions (p = 0.04). Countries in the African (0.72mm), American (0.71mm) and European (0.71mm) regions had a higher pooled mean CIMT compared to those in the South East Asian (0.62mm), West Pacific (0.60mm) and Eastern Mediterranean (0.60mm) regions. Males had a higher pooled mean CIMT of 0.06mm than females in the non CHD group (p = 0.001); there were also regional differences. The CHD group had a significantly higher mean CIMT than the non-CHD group (difference = 0.23mm, p = 0.001) with regional variations. Carotid artery segment-specific-CIMT variations are present in this population. Older persons and those having CHD group had significantly thicker CIMTs. Conclusions CIMT varies according to region, age, sex and whether a person having CHD. There are significant regional differences of mean CIMT between CHD and non-CHD groups. Segment specific CIMT variations exist among regions. There is an association between CHD and CIMT values.

multiple reports of the same study. For articles on the same population, the more comprehensive one was selected. Apart from inclusion and exclusion criteria, authors selected studies with adjusted CIMT values and study quality assessment statements were considered. When CIMT measurements were available for several time points, the time point closest to the end of the intervention or the follow-up period was selected for data extraction. When essential information was missing from the published reports, the principal investigator contacted the authors of the original studies by email or through "Research gate" to request for missing data. A maximum of two email attempts per study was made.
Study quality. The quality of selected studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria [39], the "STROBE statement" quality assessment tool and "The Newcastle-Ottawa Scale" were used to assess quality and heterogeneity of case control, cross sectional and cohort studies, and risk of bias [40]. Quality appraisal was performed independently by two reviewers. The protocol of ultrasound measurement of CIMT and reliability was assessed based on "A Consensus Statement from the American Society of Echocardiography Carotid Intima-Media Thickness Task Force" [41].

Data analysis
Data analysis was carried out using STATA version 16

Measures of association
Differences in CIMT by age, sex and selected risk factors in countries between WHO regions.
Descriptive analyses. The characteristics of the study population including details of publication, country, WHO region, age, gender, sample size, measurement site, CIMT assessment, ultrasound protocol and process, identified risk factors, factors adjusted for and adjusted predictors of CIMT in each study are presented in the text and as tables.

Steps of meta-analyses
The mean CIMT were pooled according to WHO regions. Based on the literature we expected to have heterogeneity between the pooled data [16,[41][42][43][44]. Therefore, meta-analyses were done using random-effects models with inverse variance-weighted average. Results are presented graphically as forest plots. Meta regression analysis of CIMT values was conducted with and without adjusting for coronary heart disease status, region, mean age and ultrasound technique used.
Assessment of heterogeneity of studies. Heterogeneity was tested using the Cochran's Q test and quantified using the I 2 [38]. An I 2 � 50% or p< 0.05 was considered as indicating significant heterogeneity [45]. Sensitivity analyses were carried out by excluding studies with relatively small sample sizes and low-quality studies based on the scores of QUADAS-2 criteria, "STROBE statement "and "The Newcastle-Ottawa Scale".
Assessment of strength of evidence. Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) criteria, "STROBE statement"and "The Newcastle-Ottawa Scale" were applied to evaluate the quality of the included articles [39]. QUADAS-2 criteria assess the strength of evidence by categorizing studies into low risk, high risk and unclear based on patient selection, index test, and reference standard, flow and timing domains. The "STROBE statement" checklist consists of 22 items that relate to the title, abstract, introduction, methods, results, and discussion sections of articles. Eighteen items are common to all three study designs and four are specific for cohort, case-control, or cross-sectional studies. The primary outcome was the STROBE score, defined as the number of the 22 STROBE items adequately reported divided by the number of applicable items, expressed as a percentage [46,47]. Publication quality grades of STROBE score are as follows: excellent (more than 85%), good (85 to 70%), fair (70 to 50%) and poor (less than 50%). The Newcastle-Ottawa Scale considers study selection, comparability and outcome categories when assessing the quality of selected studies. The points are considered as follows: 4 points for selection, 2 points for comparability, and 3 points for outcomes. Study quality was categorized according to total points obtained by each study (very good [9], good [7][8], satisfactory [5][6] and unsatisfactory [0][1][2][3][4] [48,49]).
Two independent reviewers conducted the full text review. The agreement between the two reviewers was 90% with a Cohen's kappa of 0.733. All the studies were evaluated using QUA-DAS-2, "STROBE statement" and "The Newcastle-Ottawa Scale" for cross sectional, case control and cohort studies, respectively. QUADAS-2 risk of bias and applicability of the selected studies is shown in Fig 2. The percentages of low-risk studies based on patient selection, index test, reference standard and flow and timing domains were 93.5%, 84.7%, 65.2% and 65.2%, respectively. In the applicability category, it was 64.4% for patient selection, 82.7% for index test and 52.2% for reference standard. 91.3% (42/46) of the studies fulfilled the criteria of the STROBE statement (S1 Table). The Newcastle-Ottawa scale was used to assess the quality of selected studies. Average total quality score for Newcastle-Ottawa scale of cross sectional, case control and cohort studies were7, 7 and 8, respectively (S2-S4 Tables, respectively). Table 1 provides an overview of the 46 studies included in the systematic review and metaanalyses. The studies were categorized based on the countries they were conducted in according to WHO regions: African Region (AFR) had6(13%) studies; Eastern Mediterranean Region (EMR) had 4(8%); European Region (EUR) had 12(26%); Region of the Americas (PAHO) had8(17%); South-East Asia Region (SEAR) had 7(15%); and the Western Pacific Region (WPR) had 9(20%) studies. There were 24(52%) cross sectional studies, 20(445%) case control studies, 01(2%) prospective study and 01(2%) retrospective cohort study included in the systematic review. There was heterogeneity when measuring the CIMT value among the studies. The commonest segment measured was the far wall of the common carotid artery (CCA) (both sides) (19/46 = 41%), followed by the far wall of CCA, carotid bulb (CB) and internal carotid artery (ICA) (both sides) (6/46 = 13%) and the far and near walls of CCA, CB and ICA (both sides) (4/46 = 9%). The most common IMT definition used was mean CIMT (30/ 46 = 65%). Definition of plaque was reported in 58% of studies (27/46). ECG gating at acquisition was reported in 28%(13/46) of studies. All studies had used a linear transducer with the frequency varying from 3MHz to 15MHz. Only five studies used Digital Imaging and Communications in Medicine (DICOM) software. Traditional modifiable risk factors were the commonest predictors of CIMT (21/46 = 45.6%) followed by non-modifiable risk factors of age and gender (13/46 = 28%). Three studies reported age as a single predictor of CIMT (3/ 46 = 7%). One study reported air pollution as a risk factor for CIMT. Three studies reported socio-economic status as a predictor of CIMT. HIV infection, CRP levels and metabolic

PLOS ONE
Regional and demographic variations of Carotid artery Intima and Media Thickness (CIMT) syndrome were reported as predictors of CIMT in a few studies. Only one study reported that none of the traditional risk factors predicted CIMT. Table 2 shows the mean CIMT values of different carotid segments by WHO region in the non-CHD and CHD groups. The mean CIMT values of CCA vary from 0.58±0.09mm to 0.74 ±0.11mm. The mean CIMT of CB ranges from 0.65±0.08mm to 0.81±0.09mm. The range for the mean CIMT of ICA was 0.65±0.10mm to 0.69±0.06. In each region, the highest mean CIMT value was in the CB followed by the CCA and the ICA. The highest mean CIMT value of CCA of 0.74±0.11mm was in EUR countries. The mean CIMT values of CCA in SEAR and
There was a significant mean difference of the pooled CIMT values between CHD and non-CHD groups (0.23mm, p = 0.001) (Fig 6). PAHO   countries had significant differences in the mean CIMT difference between the CHD and non-CHD groups within the respective region (Fig 6). Table 3 shows the summary of the Meta regression analysis of CIMT values. In the adjusted model, CHD group, WHO region and age were significantly associated with CIMT. The mean

PLOS ONE
CIMT value in the CHD group was 0.214 mm greater than that of the non-CHD group after adjusting for the other variables. The mean CIMT was significantly less among populations in SEAR and WPR as compared to populations from PAHO after adjustment. With age there was a significant increase in the mean CIMT values.

Discussion
Coronary heart disease (CHD) is the most important cause of morbidity, mortality and premature deaths of NCDs. We included 46 eligible articles comprising data of 49 381 individuals. The highest number of studies was from the European region while the lowest was from the Eastern Mediterranean region.

Modifiable risk factors
45.6% of the studies reviewed showed that modifiable risk factors were predictors of CIMT. There was a significant difference in CIMT values among the non-CHD group between regions. Higher CIMT values were observed in countries in the African, American and European regions. The mean difference in CIMT values between CHD and non-CHD groups were significantly different between and within regions. Differences in the CIMT values between regions may be due to socio-economic status [95,96], environmental conditions, smoking habits, harmful consumption of alcohol, physical activity, dietary patterns, sedentary behaviors and body mass indices [23, 24, 97-100], and prevalence of co-morbidities such as diabetes, hypertension, dyslipidemia, cancer and chronic kidney disease [101,102].
Age-adjusted cardiovascular death rates have declined in several developed countries in the past decades. In contrast, the death rates of cardiovascular disease have risen greatly in lower middle income countries [103][104][105]. Several publications underscore the high burden of disease associated with non-communicable diseases and its economic impact on lower middle income countries [4,104,106]. Due to this reason, non-communicable diseases in lower middle income countries have received increasingly more global attention by scientists, public health advocates and policy makers. A recent study has identified that NCDs and CHD risk factors such as demographic transition, environmental pollution, metabolic risk factors, lack of education, unhealthy food habits and unhealthy lifestyles have similar effects in both developed and developing countries [109].
Some studies reported that non-traditional risk factors such as HIV infection, metabolic syndrome, infections and inflammation as predictors of CIMT. Some studies have highlighted that during chronic infections and inflammation, elevated levels of the pro-inflammatory cytokines interleukin (IL)-6 and C-reactive protein (CRP) are associated with subclinical atherosclerosis [107,108]. Intima-medial thickening is a complex process. Modifiable risk factors contribute in different stages in different proportions. Factors that vary stress and blood pressure, which may cause a local delay in lumen transportation, may lead to the accumulation of potentially atherogenic particles in the arterial wall and stimulate CIM thickening and plaque formation [109]. Risk factors which cause endothelial destruction and functional abnormalities are associated with higher carotid IMT and were associated with a higher risk of atherosclerotic disease [110].

Non-modifiable risk factors
28.5% of the studies we reviewed reported that non-modifiable risk factors such as age and gender are associated with CIMT. The CIMT values of males are significantly higher than that  [111,112], inflammatory cytokines, hematological parameters [30, [112][113][114] and vitamin D [115] have been reported to be potential risk factors for increased CIMTs. In our review, we did not find these to be risk factors probably due to the specific study designs, study populations and outcomes considered by us.
The Meta regression analysis demonstrated that CIMT values were influenced by WHO region, age and CHD group. Even though there is a clear association between CIMT and CHD its usability as a risk predictor for CHD needs to be further investigated. Approaches to prevention as well as screening of at-risk populations for CHD may need to consider regional variations of CIMT.
Most studies included in this review had not documented the ethnic composition of their samples. Therefore, we were unable to evaluate CIMT variations among different ethnicities. It is reported that healthy UK black African-Caribbean children have higher CIMT levels, not explained by conventional cardiovascular risk markers, as compared to other ethnicities [116]. Ethnicity significantly modifies the associations between risk factors, CIMT values and cardiovascular events [122]; the association between CIMT and age, HDL cholesterol, total cholesterol and smoking was weaker among Blacks and Hispanics [117]. Systolic blood pressure was associated more strongly with CIMT in Asians [117]. These differences could be due to varying interactions between different risk factors and ethnicities. These differences provide insight into the etiology of cardiovascular disease among ethnic groups and aid the ethnic-specific implementation of primary prevention.

Segmental variation of CIMT
We have summarized variations in the mean CIMT values of CCA, CB and ICA within and between regions. These differences may be due to different influences of risk factors on the different segments. A Korean study reported associations between cardiovascular risk factors and different segments of the carotid artery: in men, alcohol use (CIMT at the bifurcation); physical activity (CIMT at the common and internal carotid segments); BMI (CIMT of all segments); diabetes (CIMT at the bifurcation and internal carotid segment); hypertension (CIMT at the internal carotid segment); and HDL-cholesterol (CIMT at the bifurcation and the common carotid segment): in women, smoking (CIMT at the bifurcation), hypertension (CIMT at the common carotid segment), total and LDL cholesterol (CIMT at the bifurcation and internal carotid segment), and hs-CRP (CIMT at the common and internal carotid segments) [118]. Furthermore, the Malmö Diet and Cancer Study (MDCS) reported that HDL was associated with IMT progression in the CCA but not at the bifurcation. The same showed that diabetes was associated with IMT progression at the bifurcation, but not in the CCA [119,120].
This study summarized that CIMT values of non-CHD population vary among regions. Age and gender have a significant effect on CIMT differences. Furthermore, there were marked differences of mean CIMT values between non-CHD and CHD groups. It was different from region to region as well as within regions.

Ultrasound protocol for CIMT measurement
There were variations in the ultrasound assessment of CIMT. The transducer frequency ranged from 3MHz to 15MHz; five studies used DICOM software. Variations in the ultrasonography protocol are likely to affect CIMT values. There are different arguments with regard to various ultrasound protocols during CIMT measurement [44]. Mannheim Carotid Intima-Media Thickness consensus (2004)(2005)(2006)) is a useful guideline to achieve homogeneity of CIMT measurement among studies [121]. A common protocol will ensure reproducibility and comparison of findings of different studies.
There was no uniformity in the selection of the site for measurement or the reporting of the CIMT measurement. The far wall of CCA (both sides) was the commonest site (41%) selected. The mean CIMT value was reported in 65% of studies. Plaque formation was reported in 59% of studies. It has been reported that this is unlikely to alter the results by much in populations with a low prevalence of plaque [44]. Some studies imaged only one side of the neck, whereas others imaged both sides [122]. Some included imaging of a single segment while multiple segments were imaged in others [77,123,124]. Some studies imaged the far wall of multiple segments, whereas others imaged both the near and far walls [125,126]. Studies also differed in the type of IMT measurements made and the use of different arbitrary cut-off points of CIMT to predict risk. Our review also shows that ECG gating at acquisition was reported only by 28% of studies. The phase of the cardiac cycle (end-systole vs. end-diastole) when CIMT is measured also differs among studies. Because of systolic lumen diameter expansion that leads to thinning of CIMT during systole, CIMT values obtained from end-systole are lower than those obtained in end-diastole [16]. In our meta-analysis we categorized ultrasound technique of measuring CIMT into three categories; manually, automatically and automatically with ECG gating. Literature shows that CIMT measured by General Electric (GE) semi-automated edge-detection software and Artery Measurement semi-automated software (AMS) have significant differences when measuring mean CIMT [127]. Hence, results obtained from different CIMT software systems should be compared with caution. CIMT variations using similar software may be explained by the position/angle of ultrasound transducer, and the specific combinations of segments and walls examined [128]. These factors are associated with differences in reproducibility, magnitude, and precision of progression of CIMT over time. To avoid these discrepancies, it is recommended to measure CIMT in multiple segments with different angles [128]. In our review, we found that most of the studies have obtained an average CIMT value by multiple measurements. This may be a reason that significant differences were not found when multiple segments were examined.

Conclusion
CIMT among the non-CHD group varies between and within regions, and by age and sex. The mean CIMT values between non-CHD and CHD groups were significantly different within and between WHO regions possibly due to varying influences of modifiable and non-modifiable risk factors. CHD group had a significantly thicker mean CIMT after adjusting for age, WHO region and ultrasound machine used. Segment specific CIMT variations exist among regions.

Limitation of study
Our review consisted of few studies with small sample sizes. But Egger's test showed no significant small study effect in our review. Some studies had large sample sizes which contributed most to our analyses. We were unable to capture some new risk factors such as genetic composition, immune disorders and cytokine's effect on CIMT due to the selection criteria we used. However, these studies had small sample sizes which may not have been generalizable. It is unlikely that exclusion of these risk factors would have influenced our findings.
The way we grouped countries by WHO regions may not be the most appropriate grouping to consider as WHO regions have been established taking into consideration political considerations as well. For example, the Republic of Korea (South Korea) is in the WPR whereas the Democratic People's Republic of Korea (North Korea) is in the SEAR. Similarly, Pakistan and Afghanistan, both South Asian countries, are in the EMR, though all other South Asian countries (Bangladesh, Bhutan, India, Maldives, Nepal and Sri Lanka) are in the SEAR together with Myanmar, Thailand, Indonesia and Timor Leste. Therefore, there is a likelihood of ethnic and cultural diversity influencing CIMT values among countries within regions.
Studies included in our review had not specified the ethnic composition of the study samples. Consequently, we were unable to examine CIMT variations by ethnicity. Further studies to explore this variability in future are warranted.